The association of epicardial adipose tissue measurement and severity of coronary artery disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Epicardial adipose tissue (EAT) has emerged as a significant biomarker in the assessment of coronary artery disease (CAD), particularly in the context of non-invasive imaging techniques such as computed tomography (CT) coronary angiography. The correlation between EAT volume and the severity of CAD has been the subject of numerous studies, yet the findings remain inconsistent, necessitating a systematic review and meta-analysis to elucidate this relationship. Objectives To evaluate the association between EAT volume and the severity of CAD, as assessed by computer tomographic coronary angiography. Methods This study followed the protocols specified in the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement. A comprehensive PubMed, EMBASE, and Scopus databases search of the literature assessing the association between EAT and CAD was performed. To identify and retrieve all potentially relevant articles regarding this topic, the search was performed utilizing the following expression: [(‘epicardial adipose tissue’ OR ‘epicardial fat’) AND (‘coronary artery disease’ OR ‘coronary stenosis’ OR ‘coronary atherosclerosis’ OR ‘myocardial ischemia’)]. An additional manual search was performed by analyzing the reference list of original publications and review articles. The search was restricted to articles that were published until October 2023. Animal studies, case reports, case series and reviews were excluded. Two independent reviewers screened studies, extracted data, and assessed study quality using the Newcastle-Ottawa Scale. A random-effects model using inverse variance was used to pool the effect mean size. Results A total of 30 studies, involving 10741 participants, met the inclusion criteria. The meta-analysis demonstrated that individuals with CAD had significantly higher EAT volumes compared to those with non-CAD (Mean difference: -26.93, 95% CI [-32.26, -21.61], p < 0.001). The I2 value of 96% showed the homogenous nature of the included studies. Conclusions This systematic review and meta-analysis indicate a significant positive association between EAT volume and CAD severity, suggesting that increased EAT volume may reflect a heightened atherosclerotic burden. The findings support the potential utility of EAT volume as a marker for CAD severity, with implications for risk stratification and therapeutic targeting. Further research is required to clarify the mechanisms underlying this association and to standardize EAT measurement protocols.Prisma PForest plot
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".